|
gptkbp:instance_of
|
gptkb:television_channel
|
|
gptkbp:bfsLayer
|
4
|
|
gptkbp:bfsParent
|
gptkb:Style_GAN
|
|
gptkbp:applies_to
|
Image Data
|
|
gptkbp:based_on
|
Autoregressive Models
|
|
gptkbp:can_create
|
High-Quality Images
|
|
gptkbp:developed_by
|
gptkb:Google_Brain
|
|
gptkbp:has_achievements
|
State-of-the-art Results
|
|
gptkbp:has_variants
|
gptkb:Conditional_Pixel_CNN
gptkb:Gated_Pixel_CNN
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Pixel CNN
|
|
gptkbp:improves
|
gptkb:Pixel_RNN
|
|
gptkbp:introduced
|
gptkb:2016
|
|
gptkbp:is_analyzed_in
|
gptkb:microprocessor
Unsupervised Learning
|
|
gptkbp:is_available_on
|
gptkb:archive
|
|
gptkbp:is_cited_in
|
Numerous Studies
|
|
gptkbp:is_compared_to
|
Traditional Methods
Other Neural Networks
GA Ns
VA Es
|
|
gptkbp:is_designed_for
|
Image Generation
|
|
gptkbp:is_discussed_in
|
Machine Learning Conferences
|
|
gptkbp:is_documented_in
|
Research Papers
|
|
gptkbp:is_evaluated_by
|
gptkb:Fréchet_Inception_Distance
gptkb:MNIST_Dataset
gptkb:CIFAR-10_Dataset
gptkb:Celeb_A_Dataset
Inception Score
User Studies
Visual Quality Assessment
Perplexity Metric
|
|
gptkbp:is_implemented_in
|
gptkb:Graphics_Processing_Unit
|
|
gptkbp:is_influenced_by
|
gptkb:television_channel
gptkb:Recurrent_Neural_Networks
gptkb:Variational_Autoencoders
|
|
gptkbp:is_optimized_for
|
Parallel Processing
|
|
gptkbp:is_part_of
|
gptkb:AI_Research
gptkb:Generative_Adversarial_Networks
Deep Learning Frameworks
Generative Models
|
|
gptkbp:is_related_to
|
gptkb:viewpoint
gptkb:Artificial_Intelligence
gptkb:Deep_Learning
Image Processing
|
|
gptkbp:is_scalable
|
High-Resolution Images
|
|
gptkbp:is_supported_by
|
Community Contributions
|
|
gptkbp:is_used_for
|
gptkb:museum
Feature Learning
Data Augmentation
Image Inpainting
Image Completion
Image Super-resolution
|
|
gptkbp:is_used_in
|
Generative Modeling
|
|
gptkbp:requires
|
Large Datasets
|
|
gptkbp:training
|
Maximum Likelihood Estimation
|
|
gptkbp:uses
|
Masked Convolutions
|
|
gptkbp:utilizes
|
Pixel-wise Predictions
|